Abstract
Artificial bee colony (ABC) algorithm is a relatively new optimization technique that simulates the intelligent foraging behavior of honey bee swarms. It has been applied to several optimization domains to show its efficient evolution ability. In this paper, ABC algorithm is applied for the first time to evolve a directed graph chromosome structure, which derived from a recent graph-based evolutionary algorithm called genetic network programming (GNP). Consequently, it is explored to new application domains which can be efficiently modeled by the directed graph of GNP. In this work, a problem of controlling the agents's behavior under a wellknown benchmark testbed called Tileworld are solved using the ABC-based evolution strategy. Its performance is compared with several very well-known methods for evolving computer programs, including standard GNP with crossover/mutation, genetic programming (GP) and reinforcement learning (RL).
| Original language | English |
|---|---|
| Title of host publication | International Conference on Intelligent Systems Design and Applications, ISDA |
| Publisher | IEEE Computer Society |
| Pages | 89-94 |
| Number of pages | 6 |
| Volume | 2015-January |
| ISBN (Print) | 9781479979387 |
| DOIs | |
| Publication status | Published - 2015 Mar 23 |
| Event | 2014 14th International Conference on Intelligent Systems Design and Applications, ISDA 2014 - Okinawa, Japan Duration: 2014 Nov 28 → 2014 Nov 30 |
Other
| Other | 2014 14th International Conference on Intelligent Systems Design and Applications, ISDA 2014 |
|---|---|
| Country/Territory | Japan |
| City | Okinawa |
| Period | 14/11/28 → 14/11/30 |
Keywords
- agent control
- artificial bee colony
- computer programs
- directed graph
- genetic network programming
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Signal Processing
- Control and Systems Engineering